**woodpeckR**, and kindly contributed to R-bloggers)

### Problem

Making graphics with base R is annoying for many reasons, but a big one is having to type the name of the data frame over and over again to reference different columns.

### Context

Back to our Mississippi River fish data. I’ve aggregated my sampling points into polygons, and now I want to explore some of their characteristics. To do that, I’d like to make some tables and plots, and because these are just quick, exploratory plots, I don’t feel like dealing with `ggplot`

.

Load in the data (accessible on GitHub).

# Load data from GitHub polygon <- read.csv("https://raw.githubusercontent.com/kaijagahm/general/master/polygon_sampling_data_UMR.csv") # Look at what we're dealing with dim(polygon) # How big is the data set? [1] 527 21 head(polygon, 3) # Look at the first few rows poly_id propsnag n_points habitat_code 1 P04_CFL_13 0.8 5 CFL 2 P04_CFL_14 0.2 5 CFL pool Area Perimeter max_depth 1 4 105288.80 2067.890 1.30 2 4 42668.28 1770.465 0.74 avg_depth tot_vol shoreline_density_index 1 0.3625869 33955 1.797759 2 0.3291391 5953 2.417852 pct_aqveg pct_terr pct_prm_wetf 1 19.13396 93.87983 79.67522 2 41.25270 94.76871 42.44244 med_dist_to_land med_dist_to_forest 1 34.13379 34.13379 2 18.90166 32.64112 med_current wingdam revetment tributary 1 0.02 0 1 0 2 0.02 0 0 0 pct_shallow_area 1 0.9278354 2 1.0000000

First, I’d like to see how total volume `tot_vol`

of the aquatic area scales with its `Area`

.

In base R:

# Formula notation plot(polygon$tot_vol ~ polygon$Area) # OR: # Comma notation plot(polygon$Area, polygon$tot_vol)

Either way, we get this:

Or a more informative plot, with both variables on a log scale:

plot(log(polygon$tot_vol) ~ log(polygon$Area))

This isn’t *too* too clunky, but if the data frame name or column names are long, it can get a little annoying.

### Solution

The `with()`

function allows you to specify the data frame your variables are coming from and then reference the variables with respect to the data frame, similar to the `ggplot`

argument `data =`

. Handy.

```
# Plot using the with() function
with(polygon, plot(tot_vol ~ Area))
```

You can add any other arguments inside of the function, as normal, it’s just now wrapped in `with()`

.

# Log-transform variables and make the points blue dots, because why not? with(polygon, plot(log(tot_vol) ~ log(Area), # log-transform pch = 20, # dots instead of circles col = "blue", # make the dots blue main = "Polygon volume by area, log-transformed") # title )

It’s worth noting that this works for other functions besides `plot()`

, too. Here’s an example with `table()`

: let’s look at how many sampling polygons include revetment, broken down by navigation pool (area of the river). The data set contains three navigation pools: 4, 8, and 13.

`# Two-way table by ``pool`

and `revetment`

with(polygon, table(revetment, pool))

**Outcome**

Quick plots and data manipulation made even quicker!

### Resources

Discussion of when to use `with()`

:

https://stackoverflow.com/questions/42283479/when-to-use-with-function-and-why-is-it-good

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**woodpeckR**.

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